Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.12348/4323
A New Concept for Rapid Genomic Detection of Fish Disease
dc.creator | Delamare-Deboutteville, J. | en_US |
dc.creator | Barnes, A. | en_US |
dc.creator | Wilkinson, S. | en_US |
dc.creator | Chadag, V. | en_US |
dc.creator | Huso, D. | en_US |
dc.date.accessioned | 2020-08-30T08:08:43Z | |
dc.date.available | 2020-08-30T08:08:43Z | |
dc.date.issued | 2020 | en_US |
dc.identifier.citation | Jerome Delamare-Deboutteville, Andrew Barnes (Producer), Shaun Wilkinson (Producer), Vishnumurthy Mohan Chadag (Producer), Doina Huso (Producer). (7/5/2020). A New Concept for Rapid Genomic Detection of Fish Disease. Bayan Lepas, Malaysia: WorldFish (WF) (Executive Producer). https://www.youtube.com/watch?v=iFxbodO6Fos | en_US |
dc.identifier.uri | https://hdl.handle.net/20.500.12348/4323 | |
dc.description.abstract | In 2019, a WorldFish team, led by Dr. Jerome Delamare-Deboutteville, received a CGIAR Inspire Challenge award worth USD $100,000 to test a new concept for rapid detection and diagnosis of fish disease. The project's cross-functional research team includes experts from the University of Queensland, Australia, Wilderlab, New Zealand, SAF/CEFAS center at the University of Exeter, United Kingdom, GeneSEQ, Malaysia, and Centex at University of Mahidol, Thailand. The proposed approach brings together years of fish pathogen data and combines it with new pathogen DNA sequences from infected fish. Processed using specially-designed software and machine learning tools, the data will feed a cloud-based service that can be used to accurately detect and diagnose a range of fish diseases. Critical information on how to manage the disease will then be sent back to farmers, extension workers, hatcheries, and quarantine officers in near-real time, in a user-friendly format via a smartphone. The team expects the approach will reduce the need for antibiotic treatments and ensure the right treatments are used where necessary; reduce the risk of the subsequent production cycles of fish being infected and prevent the spread of disease between farms. In addition, the system will provide scientists with useful information for vaccine development. If successful, the approach also could be used to rapidly and accurately detect and manage diseases in all farmed animals. | en_US |
dc.format | MP4 | en_US |
dc.language | en | en_US |
dc.publisher | WorldFish (WF) | en_US |
dc.rights | CC-BY-NC-ND-4.0 | en_US |
dc.subject | disease | en_US |
dc.subject | genomic tool | en_US |
dc.subject | bacterial genomics | en_US |
dc.subject | oxford nanopore technologies | en_US |
dc.subject | rapid diagnotics | en_US |
dc.subject | Fish | en_US |
dc.title | A New Concept for Rapid Genomic Detection of Fish Disease | en_US |
dc.type | Video | en_US |
cg.contributor.crp | Fish | en_US |
cg.contributor.funder | CGIAR System Organization | en_US |
cg.coverage.country | Australia | en_US |
cg.coverage.country | Bangladesh | en_US |
cg.coverage.country | Malaysia | en_US |
cg.coverage.country | New Zealand | en_US |
cg.coverage.country | Thailand | en_US |
cg.coverage.region | Australia and New Zealand | en_US |
cg.coverage.region | Southern Asia | en_US |
cg.coverage.region | South-Eastern Asia | en_US |
cg.subject.agrovoc | aquaculture | en_US |
cg.subject.agrovoc | training | en_US |
cg.subject.agrovoc | ai (artificial intelligence) | en_US |
cg.subject.agrovoc | machine learning | en_US |
cg.subject.agrovoc | fish diseases | en_US |
cg.contributor.affiliation | WorldFish | en_US |
cg.contributor.affiliation | University of Exeter | en_US |
cg.contributor.affiliation | University of Queensland | en_US |
cg.contributor.affiliation | Wilderlab NZ Ltd | en_US |
cg.contributor.affiliation | Centre for Environment, Fisheries and Aquaculture Science | en_US |
cg.contributor.affiliation | Mahidol University, Faculty of science, Center of Excellence for Shrimp Molecular Biology and Biotechnology | en_US |
cg.contributor.affiliation | Independent / Not associated | en_US |
cg.identifier.status | Open access | en_US |
cg.contribution.worldfishauthor | Delamare-Deboutteville, J. | en_US |
cg.contribution.worldfishauthor | Chadag, V. | en_US |
cg.contribution.worldfishauthor | Huso, D. | en_US |
cg.description.theme | Sustainable aquaculture | en_US |
cg.identifier.url | https://www.youtube.com/watch?v=iFxbodO6Fos | en_US |
cg.creator.id | Jerome Delamare-Deboutteville: 0000-0003-4169-2456 | en_US |
cg.creator.id | Vishnumurthy Mohan Chadag: 0000-0002-2574-284X | en_US |
cg.creator.id | Doina Huso: 0000-0002-4477-2593 | en_US |
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